做文档解析或 RAG 的团队注意了——Claude Fable 5 在推理上很强，但文档理解性价比不如 Gemini 3 Flash，甚至不如专业 OCR 服务。如果你在选模型做文档处理，这篇评测能帮你省下 10 倍 token 成本，值得点开对比。
LlamaIndex 创始人 Jerry Liu 在 X 上发布了对 Claude Fable 5 的 ParseBench 基准测试结果。该模型在推理密集型任务（如 SWE-Bench Pro、FrontierCode）上表现卓越，但在文档理解任务上仅与 Gemini 3 Flash 相当，而 token 成本却高出 10-15 倍。有趣的是，模型自身似乎也意识到这一点，在被问及最不喜欢的任务时，它表示不喜欢“请求完全明确、答案完全已知”的任务，暗示其表现不佳部分源于“懒惰”和缺乏意愿。尽管在内容忠实度（90.02%）和语义格式化（72.62%）上领先，但整体仍远逊于专业 OCR 提供商。
Claude Fable 5 thinks document parsing is beneath it It is absolutely crushing on all reasoning-int...
Claude Fable 5 thinks document parsing is beneath it It is absolutely crushing on all reasoning-intensive/long horizon benchmarks: SWE-Bench Pro, FrontierCode, GDPval, Runescape, etc. But for document understanding tasks, it is roughly equivalent with Gemini 3 Flash in performance, at roughly 10-15x the token cost. We benchmarked the model on ParseBench and compared it against all other frontier models. It is definitely up there compared to other frontier models, but falls far short of specialized OCR providers. What we found interesting is that Fable 5 is self-aware about this. When we ask the model what tasks it enjoys the last, it actively said that it dislikes tasks "where the request is fully specified and the answer is fully known" - implying part of it being bad is due to laziness and lack of willingness to actually solve the task at hand. For a full list of results across different frontier models, check out ParseBench! parsebench.ai LlamaIndex 🦙 @llama_index Day 0 Anthropic Fable 5 in ParseBench: We tested the model's advancements when it comes to document understanding. The model clearly peaks when it comes to adherence to the original text: 📃 Content faithfulness: 90.02% vs 86.19% (Gemini 3 Flash) and 86.81% (GPT-5.5) 🔢 Semantic formatting: 72.62% vs 58.35% and 60.12%, a 12+ point lead These are two of the most important metrics for SOTA document understanding: does the output preserve what the document actually says, and does it preserve formatting that carries meaning? But ... it's not a sweep there continues to be a lot of alpha in unlocking document understanding for frontier models. Full results below 👇 🔗 View Quoted Tweet 💬 2 🔄 2 ❤️ 12 👀 2574 📊 5 ⚡